Binary Image
Processing

This module presents the major components of a complete (albeit trivial) vision system.

Contents

INTRODUCTION

The simplest type of image which is used widely in a variety of industrial and medical applications is binary, i.e. a black-and-white or silhouette image. Binary image processing has several advantages but some corresponding drawbacks:

Advantages

Disadvantages

THRESHOLDING

In the simplest case, an image may consist of a single object or several separated objects of relatively high intensity, viewed against a background of relatively low intensity. This allows figure/ground separation by thresholding. In order to create the two-valued binary image a simple threshold may be applied so that all the pixels in the image plane are classified into object and background pixels. A binary image function can then be constructed such that pixels above the threshold are foreground (``1'') and below the threshold are background (``0'').

You can see the effect of thresholding by moving the slider in this applet. The slider sets the threshold and the image on the right shows the result and binary image. In this case, white pixels are above the threshold and black are below it.

Exercise 1: This image is of a white square against a black background. Try to find a threshold which makes the square completely white and the background completely black.

Exercise 2: This image is of a bracket and a J-clamp. Try to find a threshold which separates the bracket from both the clamp and the background. Then try to separate the objects from the background.

[ Aids to threshold selection: histograms. ]

Author:: Andrew Fitzgibbon at the Department of Artificial Intelligence, University of Edinburgh